Dataset statistics
| Number of variables | 9 |
|---|---|
| Number of observations | 500 |
| Missing cells | 40 |
| Missing cells (%) | 0.9% |
| Duplicate rows | 0 |
| Duplicate rows (%) | 0.0% |
| Total size in memory | 35.3 KiB |
| Average record size in memory | 72.3 B |
Variable types
| Numeric | 7 |
|---|---|
| Categorical | 2 |
GRE Score is highly overall correlated with TOEFL Score and 4 other fields | High correlation |
TOEFL Score is highly overall correlated with GRE Score and 6 other fields | High correlation |
SOP is highly overall correlated with TOEFL Score and 4 other fields | High correlation |
LOR is highly overall correlated with TOEFL Score and 3 other fields | High correlation |
CGPA is highly overall correlated with GRE Score and 5 other fields | High correlation |
Chance of Admit is highly overall correlated with GRE Score and 6 other fields | High correlation |
Research is highly overall correlated with GRE Score and 3 other fields | High correlation |
University Rating is highly overall correlated with GRE Score and 5 other fields | High correlation |
GRE Score has 15 (3.0%) missing values | Missing |
TOEFL Score has 10 (2.0%) missing values | Missing |
University Rating has 15 (3.0%) missing values | Missing |
Serial No. is uniformly distributed | Uniform |
Serial No. has unique values | Unique |
Reproduction
| Analysis started | 2022-12-11 22:33:43.089306 |
|---|---|
| Analysis finished | 2022-12-11 22:33:53.566790 |
| Duration | 10.48 seconds |
| Software version | pandas-profiling vv3.5.0 |
| Download configuration | config.json |
| Distinct | 500 |
|---|---|
| Distinct (%) | 100.0% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 250.5 |
| Minimum | 1 |
|---|---|
| Maximum | 500 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 4.0 KiB |
Quantile statistics
| Minimum | 1 |
|---|---|
| 5-th percentile | 25.95 |
| Q1 | 125.75 |
| median | 250.5 |
| Q3 | 375.25 |
| 95-th percentile | 475.05 |
| Maximum | 500 |
| Range | 499 |
| Interquartile range (IQR) | 249.5 |
Descriptive statistics
| Standard deviation | 144.48183 |
|---|---|
| Coefficient of variation (CV) | 0.57677378 |
| Kurtosis | -1.2 |
| Mean | 250.5 |
| Median Absolute Deviation (MAD) | 125 |
| Skewness | 0 |
| Sum | 125250 |
| Variance | 20875 |
| Monotonicity | Strictly increasing |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 1 | 1 | 0.2% |
| 330 | 1 | 0.2% |
| 343 | 1 | 0.2% |
| 342 | 1 | 0.2% |
| 341 | 1 | 0.2% |
| 340 | 1 | 0.2% |
| 339 | 1 | 0.2% |
| 338 | 1 | 0.2% |
| 337 | 1 | 0.2% |
| 336 | 1 | 0.2% |
| Other values (490) | 490 |
| Value | Count | Frequency (%) |
| 1 | 1 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 1 |
| Value | Count | Frequency (%) |
| 500 | 1 | |
| 499 | 1 | |
| 498 | 1 | |
| 497 | 1 | |
| 496 | 1 | |
| 495 | 1 | |
| 494 | 1 | |
| 493 | 1 | |
| 492 | 1 | |
| 491 | 1 |
| Distinct | 49 |
|---|---|
| Distinct (%) | 10.1% |
| Missing | 15 |
| Missing (%) | 3.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 316.55876 |
| Minimum | 290 |
|---|---|
| Maximum | 340 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 4.0 KiB |
Quantile statistics
| Minimum | 290 |
|---|---|
| 5-th percentile | 298 |
| Q1 | 308 |
| median | 317 |
| Q3 | 325 |
| 95-th percentile | 335 |
| Maximum | 340 |
| Range | 50 |
| Interquartile range (IQR) | 17 |
Descriptive statistics
| Standard deviation | 11.274704 |
|---|---|
| Coefficient of variation (CV) | 0.035616466 |
| Kurtosis | -0.68446669 |
| Mean | 316.55876 |
| Median Absolute Deviation (MAD) | 8 |
| Skewness | -0.051686583 |
| Sum | 153531 |
| Variance | 127.11896 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=49)
| Value | Count | Frequency (%) |
| 324 | 22 | 4.4% |
| 312 | 22 | 4.4% |
| 322 | 17 | 3.4% |
| 327 | 17 | 3.4% |
| 316 | 17 | 3.4% |
| 321 | 17 | 3.4% |
| 320 | 16 | 3.2% |
| 314 | 16 | 3.2% |
| 311 | 16 | 3.2% |
| 325 | 15 | 3.0% |
| Other values (39) | 310 |
| Value | Count | Frequency (%) |
| 290 | 2 | 0.4% |
| 293 | 1 | 0.2% |
| 294 | 2 | 0.4% |
| 295 | 5 | |
| 296 | 5 | |
| 297 | 6 | |
| 298 | 10 | |
| 299 | 8 | |
| 300 | 12 | |
| 301 | 10 |
| Value | Count | Frequency (%) |
| 340 | 9 | |
| 339 | 3 | 0.6% |
| 338 | 4 | |
| 337 | 2 | 0.4% |
| 336 | 5 | |
| 335 | 4 | |
| 334 | 7 | |
| 333 | 4 | |
| 332 | 7 | |
| 331 | 9 |
| Distinct | 29 |
|---|---|
| Distinct (%) | 5.9% |
| Missing | 10 |
| Missing (%) | 2.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 107.18776 |
| Minimum | 92 |
|---|---|
| Maximum | 120 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 4.0 KiB |
Quantile statistics
| Minimum | 92 |
|---|---|
| 5-th percentile | 98 |
| Q1 | 103 |
| median | 107 |
| Q3 | 112 |
| 95-th percentile | 118 |
| Maximum | 120 |
| Range | 28 |
| Interquartile range (IQR) | 9 |
Descriptive statistics
| Standard deviation | 6.1128994 |
|---|---|
| Coefficient of variation (CV) | 0.057029829 |
| Kurtosis | -0.66456537 |
| Mean | 107.18776 |
| Median Absolute Deviation (MAD) | 5 |
| Skewness | 0.10206773 |
| Sum | 52522 |
| Variance | 37.367539 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=29)
| Value | Count | Frequency (%) |
| 110 | 42 | 8.4% |
| 105 | 37 | 7.4% |
| 104 | 29 | 5.8% |
| 107 | 28 | 5.6% |
| 112 | 27 | 5.4% |
| 106 | 26 | 5.2% |
| 103 | 25 | 5.0% |
| 102 | 24 | 4.8% |
| 100 | 24 | 4.8% |
| 99 | 22 | 4.4% |
| Other values (19) | 206 |
| Value | Count | Frequency (%) |
| 92 | 1 | 0.2% |
| 93 | 2 | 0.4% |
| 94 | 2 | 0.4% |
| 95 | 3 | 0.6% |
| 96 | 6 | 1.2% |
| 97 | 7 | 1.4% |
| 98 | 10 | |
| 99 | 22 | |
| 100 | 24 | |
| 101 | 19 |
| Value | Count | Frequency (%) |
| 120 | 9 | 1.8% |
| 119 | 10 | 2.0% |
| 118 | 10 | 2.0% |
| 117 | 8 | 1.6% |
| 116 | 16 | |
| 115 | 11 | |
| 114 | 18 | |
| 113 | 18 | |
| 112 | 27 | |
| 111 | 20 |
| Distinct | 5 |
|---|---|
| Distinct (%) | 1.0% |
| Missing | 15 |
| Missing (%) | 3.0% |
| Memory size | 4.0 KiB |
| 3.0 | |
|---|---|
| 2.0 | |
| 4.0 | |
| 5.0 | |
| 1.0 |
Length
| Max length | 3 |
|---|---|
| Median length | 3 |
| Mean length | 3 |
| Min length | 3 |
Characters and Unicode
| Total characters | 1455 |
|---|---|
| Distinct characters | 7 |
| Distinct categories | 2 ? |
| Distinct scripts | 1 ? |
| Distinct blocks | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | 4.0 |
|---|---|
| 2nd row | 4.0 |
| 3rd row | 3.0 |
| 4th row | 3.0 |
| 5th row | 2.0 |
Common Values
| Value | Count | Frequency (%) |
| 3.0 | 154 | |
| 2.0 | 124 | |
| 4.0 | 103 | |
| 5.0 | 72 | |
| 1.0 | 32 | 6.4% |
| (Missing) | 15 | 3.0% |
Length
Histogram of lengths of the category
Common Values (Plot)
| Value | Count | Frequency (%) |
| 3.0 | 154 | |
| 2.0 | 124 | |
| 4.0 | 103 | |
| 5.0 | 72 | |
| 1.0 | 32 | 6.6% |
Most occurring characters
| Value | Count | Frequency (%) |
| . | 485 | |
| 0 | 485 | |
| 3 | 154 | 10.6% |
| 2 | 124 | 8.5% |
| 4 | 103 | 7.1% |
| 5 | 72 | 4.9% |
| 1 | 32 | 2.2% |
Most occurring categories
| Value | Count | Frequency (%) |
| Decimal Number | 970 | |
| Other Punctuation | 485 |
Most frequent character per category
Decimal Number
| Value | Count | Frequency (%) |
| 0 | 485 | |
| 3 | 154 | 15.9% |
| 2 | 124 | 12.8% |
| 4 | 103 | 10.6% |
| 5 | 72 | 7.4% |
| 1 | 32 | 3.3% |
Other Punctuation
| Value | Count | Frequency (%) |
| . | 485 |
Most occurring scripts
| Value | Count | Frequency (%) |
| Common | 1455 |
Most frequent character per script
Common
| Value | Count | Frequency (%) |
| . | 485 | |
| 0 | 485 | |
| 3 | 154 | 10.6% |
| 2 | 124 | 8.5% |
| 4 | 103 | 7.1% |
| 5 | 72 | 4.9% |
| 1 | 32 | 2.2% |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 1455 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| . | 485 | |
| 0 | 485 | |
| 3 | 154 | 10.6% |
| 2 | 124 | 8.5% |
| 4 | 103 | 7.1% |
| 5 | 72 | 4.9% |
| 1 | 32 | 2.2% |
SOP
Real number (ℝ)
| Distinct | 9 |
|---|---|
| Distinct (%) | 1.8% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 3.374 |
| Minimum | 1 |
|---|---|
| Maximum | 5 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 4.0 KiB |
Quantile statistics
| Minimum | 1 |
|---|---|
| 5-th percentile | 1.5 |
| Q1 | 2.5 |
| median | 3.5 |
| Q3 | 4 |
| 95-th percentile | 5 |
| Maximum | 5 |
| Range | 4 |
| Interquartile range (IQR) | 1.5 |
Descriptive statistics
| Standard deviation | 0.99100362 |
|---|---|
| Coefficient of variation (CV) | 0.29371773 |
| Kurtosis | -0.70571695 |
| Mean | 3.374 |
| Median Absolute Deviation (MAD) | 0.5 |
| Skewness | -0.2289724 |
| Sum | 1687 |
| Variance | 0.98208818 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=9)
| Value | Count | Frequency (%) |
| 4 | 89 | |
| 3.5 | 88 | |
| 3 | 80 | |
| 2.5 | 64 | |
| 4.5 | 63 | |
| 2 | 43 | |
| 5 | 42 | |
| 1.5 | 25 | 5.0% |
| 1 | 6 | 1.2% |
| Value | Count | Frequency (%) |
| 1 | 6 | 1.2% |
| 1.5 | 25 | 5.0% |
| 2 | 43 | |
| 2.5 | 64 | |
| 3 | 80 | |
| 3.5 | 88 | |
| 4 | 89 | |
| 4.5 | 63 | |
| 5 | 42 |
| Value | Count | Frequency (%) |
| 5 | 42 | |
| 4.5 | 63 | |
| 4 | 89 | |
| 3.5 | 88 | |
| 3 | 80 | |
| 2.5 | 64 | |
| 2 | 43 | |
| 1.5 | 25 | 5.0% |
| 1 | 6 | 1.2% |
LOR
Real number (ℝ)
| Distinct | 9 |
|---|---|
| Distinct (%) | 1.8% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 3.484 |
| Minimum | 1 |
|---|---|
| Maximum | 5 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 4.0 KiB |
Quantile statistics
| Minimum | 1 |
|---|---|
| 5-th percentile | 2 |
| Q1 | 3 |
| median | 3.5 |
| Q3 | 4 |
| 95-th percentile | 5 |
| Maximum | 5 |
| Range | 4 |
| Interquartile range (IQR) | 1 |
Descriptive statistics
| Standard deviation | 0.92544957 |
|---|---|
| Coefficient of variation (CV) | 0.26562847 |
| Kurtosis | -0.74574851 |
| Mean | 3.484 |
| Median Absolute Deviation (MAD) | 0.5 |
| Skewness | -0.14529031 |
| Sum | 1742 |
| Variance | 0.85645691 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=9)
| Value | Count | Frequency (%) |
| 3 | 99 | |
| 4 | 94 | |
| 3.5 | 86 | |
| 4.5 | 63 | |
| 2.5 | 50 | |
| 5 | 50 | |
| 2 | 46 | |
| 1.5 | 11 | 2.2% |
| 1 | 1 | 0.2% |
| Value | Count | Frequency (%) |
| 1 | 1 | 0.2% |
| 1.5 | 11 | 2.2% |
| 2 | 46 | |
| 2.5 | 50 | |
| 3 | 99 | |
| 3.5 | 86 | |
| 4 | 94 | |
| 4.5 | 63 | |
| 5 | 50 |
| Value | Count | Frequency (%) |
| 5 | 50 | |
| 4.5 | 63 | |
| 4 | 94 | |
| 3.5 | 86 | |
| 3 | 99 | |
| 2.5 | 50 | |
| 2 | 46 | |
| 1.5 | 11 | 2.2% |
| 1 | 1 | 0.2% |
CGPA
Real number (ℝ)
| Distinct | 184 |
|---|---|
| Distinct (%) | 36.8% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 8.57644 |
| Minimum | 6.8 |
|---|---|
| Maximum | 9.92 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 4.0 KiB |
Quantile statistics
| Minimum | 6.8 |
|---|---|
| 5-th percentile | 7.638 |
| Q1 | 8.1275 |
| median | 8.56 |
| Q3 | 9.04 |
| 95-th percentile | 9.6 |
| Maximum | 9.92 |
| Range | 3.12 |
| Interquartile range (IQR) | 0.9125 |
Descriptive statistics
| Standard deviation | 0.6048128 |
|---|---|
| Coefficient of variation (CV) | 0.070520263 |
| Kurtosis | -0.5612784 |
| Mean | 8.57644 |
| Median Absolute Deviation (MAD) | 0.46 |
| Skewness | -0.026612517 |
| Sum | 4288.22 |
| Variance | 0.36579852 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 8.76 | 9 | 1.8% |
| 8 | 9 | 1.8% |
| 8.56 | 7 | 1.4% |
| 8.12 | 7 | 1.4% |
| 8.45 | 7 | 1.4% |
| 8.54 | 7 | 1.4% |
| 8.66 | 6 | 1.2% |
| 8.65 | 6 | 1.2% |
| 8.64 | 6 | 1.2% |
| 8.5 | 6 | 1.2% |
| Other values (174) | 430 |
| Value | Count | Frequency (%) |
| 6.8 | 1 | |
| 7.2 | 1 | |
| 7.21 | 1 | |
| 7.23 | 1 | |
| 7.25 | 1 | |
| 7.28 | 1 | |
| 7.3 | 1 | |
| 7.34 | 2 | |
| 7.36 | 1 | |
| 7.4 | 1 |
| Value | Count | Frequency (%) |
| 9.92 | 1 | 0.2% |
| 9.91 | 1 | 0.2% |
| 9.87 | 2 | |
| 9.86 | 1 | 0.2% |
| 9.82 | 1 | 0.2% |
| 9.8 | 3 | |
| 9.78 | 1 | 0.2% |
| 9.76 | 2 | |
| 9.74 | 1 | 0.2% |
| 9.7 | 2 |
Research
Categorical
| Distinct | 2 |
|---|---|
| Distinct (%) | 0.4% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 4.0 KiB |
| 1 | |
|---|---|
| 0 |
Length
| Max length | 1 |
|---|---|
| Median length | 1 |
| Mean length | 1 |
| Min length | 1 |
Characters and Unicode
| Total characters | 500 |
|---|---|
| Distinct characters | 2 |
| Distinct categories | 1 ? |
| Distinct scripts | 1 ? |
| Distinct blocks | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | 1 |
|---|---|
| 2nd row | 1 |
| 3rd row | 1 |
| 4th row | 1 |
| 5th row | 0 |
Common Values
| Value | Count | Frequency (%) |
| 1 | 280 | |
| 0 | 220 |
Length
Histogram of lengths of the category
Common Values (Plot)
| Value | Count | Frequency (%) |
| 1 | 280 | |
| 0 | 220 |
Most occurring characters
| Value | Count | Frequency (%) |
| 1 | 280 | |
| 0 | 220 |
Most occurring categories
| Value | Count | Frequency (%) |
| Decimal Number | 500 |
Most frequent character per category
Decimal Number
| Value | Count | Frequency (%) |
| 1 | 280 | |
| 0 | 220 |
Most occurring scripts
| Value | Count | Frequency (%) |
| Common | 500 |
Most frequent character per script
Common
| Value | Count | Frequency (%) |
| 1 | 280 | |
| 0 | 220 |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 500 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| 1 | 280 | |
| 0 | 220 |
Chance of Admit
Real number (ℝ)
| Distinct | 61 |
|---|---|
| Distinct (%) | 12.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 0.72174 |
| Minimum | 0.34 |
|---|---|
| Maximum | 0.97 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 4.0 KiB |
Quantile statistics
| Minimum | 0.34 |
|---|---|
| 5-th percentile | 0.47 |
| Q1 | 0.63 |
| median | 0.72 |
| Q3 | 0.82 |
| 95-th percentile | 0.94 |
| Maximum | 0.97 |
| Range | 0.63 |
| Interquartile range (IQR) | 0.19 |
Descriptive statistics
| Standard deviation | 0.1411404 |
|---|---|
| Coefficient of variation (CV) | 0.19555575 |
| Kurtosis | -0.4546818 |
| Mean | 0.72174 |
| Median Absolute Deviation (MAD) | 0.1 |
| Skewness | -0.28996621 |
| Sum | 360.87 |
| Variance | 0.019920614 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 0.71 | 23 | 4.6% |
| 0.64 | 19 | 3.8% |
| 0.73 | 18 | 3.6% |
| 0.79 | 16 | 3.2% |
| 0.72 | 16 | 3.2% |
| 0.78 | 15 | 3.0% |
| 0.76 | 14 | 2.8% |
| 0.7 | 13 | 2.6% |
| 0.68 | 13 | 2.6% |
| 0.8 | 13 | 2.6% |
| Other values (51) | 340 |
| Value | Count | Frequency (%) |
| 0.34 | 2 | 0.4% |
| 0.36 | 2 | 0.4% |
| 0.37 | 1 | 0.2% |
| 0.38 | 2 | 0.4% |
| 0.39 | 1 | 0.2% |
| 0.42 | 4 | |
| 0.43 | 1 | 0.2% |
| 0.44 | 3 | |
| 0.45 | 3 | |
| 0.46 | 5 |
| Value | Count | Frequency (%) |
| 0.97 | 4 | 0.8% |
| 0.96 | 8 | |
| 0.95 | 5 | 1.0% |
| 0.94 | 13 | |
| 0.93 | 12 | |
| 0.92 | 9 | |
| 0.91 | 10 | |
| 0.9 | 9 | |
| 0.89 | 11 | |
| 0.88 | 4 | 0.8% |
Auto
The auto setting is an interpretable pairwise column metric of the following mapping:- Variable_type-Variable_type : Method, Range
- Categorical-Categorical : Cramer's V, [0,1]
- Numerical-Categorical : Cramer's V, [0,1] (using a discretized numerical column)
- Numerical-Numerical : Spearman's ρ, [-1,1]
This configuration uses the recommended metric for each pair of columns.
Spearman's ρ
The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
Pearson's r
The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
Kendall's τ
Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
Cramér's V (φc)
Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.Phik (φk)
Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here. A simple visualization of nullity by column.
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
| Serial No. | GRE Score | TOEFL Score | University Rating | SOP | LOR | CGPA | Research | Chance of Admit | |
|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 337.0 | 118.0 | 4.0 | 4.5 | 4.5 | 9.65 | 1 | 0.92 |
| 1 | 2 | 324.0 | 107.0 | 4.0 | 4.0 | 4.5 | 8.87 | 1 | 0.76 |
| 2 | 3 | NaN | 104.0 | 3.0 | 3.0 | 3.5 | 8.00 | 1 | 0.72 |
| 3 | 4 | 322.0 | 110.0 | 3.0 | 3.5 | 2.5 | 8.67 | 1 | 0.80 |
| 4 | 5 | 314.0 | 103.0 | 2.0 | 2.0 | 3.0 | 8.21 | 0 | 0.65 |
| 5 | 6 | 330.0 | 115.0 | 5.0 | 4.5 | 3.0 | 9.34 | 1 | 0.90 |
| 6 | 7 | 321.0 | 109.0 | NaN | 3.0 | 4.0 | 8.20 | 1 | 0.75 |
| 7 | 8 | 308.0 | 101.0 | 2.0 | 3.0 | 4.0 | 7.90 | 0 | 0.68 |
| 8 | 9 | 302.0 | 102.0 | 1.0 | 2.0 | 1.5 | 8.00 | 0 | 0.50 |
| 9 | 10 | 323.0 | 108.0 | 3.0 | 3.5 | 3.0 | 8.60 | 0 | 0.45 |
| Serial No. | GRE Score | TOEFL Score | University Rating | SOP | LOR | CGPA | Research | Chance of Admit | |
|---|---|---|---|---|---|---|---|---|---|
| 490 | 491 | 307.0 | 105.0 | 2.0 | 2.5 | 4.5 | 8.12 | 1 | 0.67 |
| 491 | 492 | 297.0 | 99.0 | 4.0 | 3.0 | 3.5 | 7.81 | 0 | 0.54 |
| 492 | 493 | 298.0 | 101.0 | 4.0 | 2.5 | 4.5 | 7.69 | 1 | 0.53 |
| 493 | 494 | 300.0 | 95.0 | 2.0 | 3.0 | 1.5 | 8.22 | 1 | 0.62 |
| 494 | 495 | 301.0 | 99.0 | 3.0 | 2.5 | 2.0 | 8.45 | 1 | 0.68 |
| 495 | 496 | 332.0 | 108.0 | 5.0 | 4.5 | 4.0 | 9.02 | 1 | 0.87 |
| 496 | 497 | 337.0 | 117.0 | 5.0 | 5.0 | 5.0 | 9.87 | 1 | 0.96 |
| 497 | 498 | 330.0 | 120.0 | 5.0 | 4.5 | 5.0 | 9.56 | 1 | 0.93 |
| 498 | 499 | 312.0 | 103.0 | 4.0 | 4.0 | 5.0 | 8.43 | 0 | 0.73 |
| 499 | 500 | 327.0 | 113.0 | 4.0 | 4.5 | 4.5 | 9.04 | 0 | 0.84 |